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            <h1 id="seo-header">2024泰迪杯数据挖掘比赛B题备战</h1>
            
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                    本文最后更新于 2024-03-20T17:11:59+08:00
                  
                  

                
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                <h1>前言</h1>
<p>此篇是我准备参加2024泰迪杯数据挖掘比赛所做的记录</p>
<h2 id="2024-3-19-记录">2024.3.19 记录</h2>
<p>针对B题题目核心问题需求：图文检索</p>
<p>给定输入image A-------&gt;检索输出与image A 相匹配的文本</p>
<p>给定输入text B----------&gt;检索输出与text B相匹配的image</p>
<p>基本思路：</p>
<p>找出一些最新or最近研究解决此问题的论文，最好有代码的，之后尝试复现推理其模型，在此基础上，将输入对标为赛题提供的数据，并加以修改和优化模型，然后就可以写论文上交了。</p>
<p>目前准备复现的论文：<a target="_blank" rel="noopener" href="https://hexiangteng.github.io/papers/TOMM%202023%20MKVSE.pdf">MKVSE: Multimodal Knowledge Enhanced Visual-semantic Embedding for Image-text Retrieval</a></p>
<h1><a target="_blank" rel="noopener" href="https://arxiv.org/abs/2403.05261">Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval</a></h1>
<p>任务计划：</p>
<ol>
<li>部署环境  🆗</li>
<li>用Flickr30k Dataset （复现实验结果）推理
<ul>
<li>按照要求 把文件放在指定的位置</li>
<li>指定数据集的路径修改</li>
<li>会存在若干问题</li>
<li><em>出实验结果</em></li>
</ul>
</li>
<li><strong>想办法把赛题的数据集  对齐  为Flickr30k Dataset</strong></li>
<li>使用赛题的数据对模型进行train</li>
<li>优化实验结果，1）对数据的处理  2）对模型进行修改</li>
<li><strong>展示实验结果，并且根据题目的要求提供他要求的结果表</strong></li>
<li>撰写论文</li>
</ol>
<h2 id="环境部署">环境部署</h2>
<ol>
<li>按照要求，在服务器搭建环境。创建conda 虚拟环境的同时安装依赖。<code>conda env create -f environment.yml</code>    🆗</li>
<li>在pycharm上建立远程链接服务器的依赖环境     🆗</li>
</ol>
<h2 id="数据准备">数据准备</h2>
<img src="/2024/03/19/2024%E6%B3%B0%E8%BF%AA%E6%9D%AF%E6%95%B0%E6%8D%AE%E6%8C%96%E6%8E%98%E6%AF%94%E8%B5%9BB%E9%A2%98%E5%A4%87%E6%88%98/image-20240319142848540.png" srcset="/img/loading.gif" lazyload class="" title="image-20240319142848540">
<ol>
<li><code>f30k_concepts_glove_word2vec.pkl</code> 和<code>f30k_adj_concepts.pkl</code> 都已经存在作者的项目文件夹里了   🆗   缺失一些关键数据，比如json，或模型<a target="_blank" rel="noopener" href="https://github.com/BruceW91/CVSE/tree/master">在这下</a></li>
<li><code>VisualGenome</code> 这个下面的元数据也有了，也不需要下载了   🆗</li>
<li>下载Flickr30K图片预处理的特征文件和词汇表<code>train_ids.txt</code>、<code>train_caps.txt</code>    <a target="_blank" rel="noopener" href="https://www.kaggle.com/datasets/kuanghueilee/scan-features">下载地址</a>   🆗</li>
</ol>
<p>按照要求放置好，如下图目录：</p>
<img src="/2024/03/19/2024%E6%B3%B0%E8%BF%AA%E6%9D%AF%E6%95%B0%E6%8D%AE%E6%8C%96%E6%8E%98%E6%AF%94%E8%B5%9BB%E9%A2%98%E5%A4%87%E6%88%98/image-20240319143001490.png" srcset="/img/loading.gif" lazyload class="" title="image-20240319143001490">
<h2 id="执行训练">执行训练</h2>
<h2 id="环境准备">环境准备</h2>
<p>换篇论文，那篇要的cuda版本太低了，垃圾！</p>

                
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